IEEE Transactions on Image Processing · 2012 · 125 citations · 26 references
ArtsComputer ScienceComputer VisionDigital ImagingMachine VisionDigital Image ProcessingDigital Signal ProcessingImage FilteringImage ProcessingBilateral FilteringNon-local Means FilteringNonlocal Means Filtering
A direct implementation of the bilateral filter requires O(σ(s)(2)) operations per pixel, where σ(s) is the (effective) width of the spatial kernel. A fast implementation of the bilateral filter that required O(1) operations per pixel with respect to σ(s) was recently proposed. This was done by using trigonometric functions for the range kernel of the bilateral filter, and by exploiting their so-called shiftability property. In particular, a fast implementation of the Gaussian bilateral filter was realized by approximating the Gaussian range kernel using raised cosines. Later, it was demonstrated that this idea could be extended to a larger class of filters, including the popular non-local means filter. As already observed, a flip side of this approach was that the run time depended on the width σ(r) of the range kernel. For an image with dynamic range [0,T], the run time scaled as O(T(2)/σ(2)(r)) with σ(r). This made it difficult to implement narrow range kernels, particularly for images with large dynamic range. In this paper, we discuss this problem, and propose some simple steps to accelerate the implementation, in general, and for small σ(r) in particular. We provide some experimental results to demonstrate the acceleration that is achieved using these modifications.
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Bilateral filtering for gray and color images
Carlo Tomasi, Roberto Manduchi · 2002 · 8.1K citations
Arts, Vision Science, Color Vision +16
Fast bilateral filtering for the display of high-dynamic-range images
Frédo Durand, Julie Dorsey · 2002 · 1.5K citations
Summed-area tables for texture mapping
Franklin C. Crow · 1984 · 1.1K citations
Summed-area tables for texture mapping
Franklin C. Crow · ACM SIGGRAPH Computer Graphics · 1984 · 652 citations